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Deep Learning: Zero to One
Sam Putnam
3 episodes
4 months ago
Find me on Github/Twitter/Kaggle @SamDeepLearning. Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning | Cambridge/Boston | New York City | Hanover, NH | http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant serving Boston and New York City. If you like Talking Machines, harvardnlp, CS231n, the Media Lab, CSAIL, karpathy.github.io, FAIR, Google Brain, Deeplearning4j, TensorFlow, Amazon Web Services, or Google Cloud Platform, you will like the podcast. Try it. Tweet at @SamDeepLearning if you have questions & to correct me!
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Technology
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All content for Deep Learning: Zero to One is the property of Sam Putnam and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Find me on Github/Twitter/Kaggle @SamDeepLearning. Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning | Cambridge/Boston | New York City | Hanover, NH | http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant serving Boston and New York City. If you like Talking Machines, harvardnlp, CS231n, the Media Lab, CSAIL, karpathy.github.io, FAIR, Google Brain, Deeplearning4j, TensorFlow, Amazon Web Services, or Google Cloud Platform, you will like the podcast. Try it. Tweet at @SamDeepLearning if you have questions & to correct me!
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Technology
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Music Generation - Google Magenta Best Demo NIPS 2016 LSTM RNN - Deep Learning: Zero to One
Deep Learning: Zero to One
1 hour 9 minutes
8 years ago
Music Generation - Google Magenta Best Demo NIPS 2016 LSTM RNN - Deep Learning: Zero to One
I talk through generating 10 melodies, two of which I play at the conclusion using a model trained on thousands of midi examples contained in a .mag Magenta file bundle. I used the Biaxial RNN (https://github.com/hexahedria/biaxial-rnn-music-composition) by a student named Daniel Johnson and the Basic RNN (https://github.com/tensorflow/magenta/tree/master/magenta/models/melody_rnn#basic) by Google's Magenta group within TensorFlow and learned that priming a melody with a single note can set the key for each generated melody, and, Anaconda's single 'source activate' line replaces the need for virtualenv and installs all of the necessary dependencies to make this environment easily reproducible. 2 - 3 more details are posted at: https://medium.com/@SamPutnam/deep-learning-zero-to-one-music-generation-46c9a7d82c02
Deep Learning: Zero to One
Find me on Github/Twitter/Kaggle @SamDeepLearning. Find me on LinkedIn @SamPutnam. This Podcast is supported by Enterprise Deep Learning | Cambridge/Boston | New York City | Hanover, NH | http://www.EnterpriseDeepLearning.com. Contact: Sam@EDeepLearning.com, 802-299-1240, P.O. Box 863, Hanover, NH, USA, 03755. We move deep learning to production. I teach the worldwide Deploying Deep Learning Masterclass at http://www.DeepLearningConf.com in NYC regularly and am a Deep Learning Consultant serving Boston and New York City. If you like Talking Machines, harvardnlp, CS231n, the Media Lab, CSAIL, karpathy.github.io, FAIR, Google Brain, Deeplearning4j, TensorFlow, Amazon Web Services, or Google Cloud Platform, you will like the podcast. Try it. Tweet at @SamDeepLearning if you have questions & to correct me!